Data Mining of Heterogeneous Electrical Conduction in the Electrode Components of Fuel Cells

Abstract

The electrodes of a polymer electrolyte membrane fuel cell (PEMFC) primarily contain a Pt/C catalyst and Nafion binder. Since these components play crucial roles in the redox reaction and proton transport, respectively, their distributions can directly affect the electrochemical reactivity and thus the device performance. Although analyzing the component distribution is important to understand its electrochemical reactivity and improve the device performance, determining it for the PEMFC electrode remains a challenging task. Herein, we propose a strategy for visualizing the spatial distribution of the electrode components and their heterogeneous electrical properties using multidimensional current–voltage (I–V) spectroscopy combined with data mining. The electrical properties of the electrode components, i.e., the Pt/C catalyst and Nafion binder, were explored by I–V spectroscopy, and their electrical heterogeneity was spatially classified based on the shapes of the measured I–V curves by cluster analysis. The results show that the components and their interfacial structure can be spatially visualized from the surface electrical heterogeneity. The proposed method is expected to be applicable for investigating in detail not only the spatial properties of PEMFC electrodes but also the properties of various material systems.

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